• DocumentCode
    1894628
  • Title

    A Novel Skin Tone Detection Algorithm for Contraband Image Analysis

  • Author

    Choudhury, Abhishek ; Rogers, Marcus ; Gillam, Blair ; Watson, Keith

  • Author_Institution
    Purdue Cyber Forensics Lab., West Lafayette, IN
  • fYear
    2008
  • fDate
    22-22 May 2008
  • Firstpage
    3
  • Lastpage
    9
  • Abstract
    This paper examines skin tone detection algorithms used by first responder forensic tools such as File Hound. File Hound is a "field analysis" software application that is currently being used by over 100 law enforcement agencies, both internationally and domestically. It is mainly used in forensic investigations to search and identify pornographic images from a hard drive. Since the conception of File Hound, several steps have been taken to improve its performance and expand its features. One such feature is a skin tone detection filter that can identify images with a large skin color count from the aggregate image results found by File Hound. This filter is based on the idea that there is a positive correlation between images with a large skin color count and images that are pornographic in nature. A novel skin tone detection filter was developed and this filter was tested against random images obtained from the Compaq Image database for skin tone detection. The results of the test are encouraging in terms of accuracy and low error rates: type I = 20.64%, type II = 0.81%, accuracy = 78.55%.
  • Keywords
    filtering theory; image colour analysis; skin; File Hound; contraband image analysis; field analysis software; forensic investigations; hard drive; pornographic image; skin color; skin tone detection filter; Aggregates; Application software; Detection algorithms; Filters; Forensics; Image analysis; Image color analysis; Law enforcement; Skin; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systematic Approaches to Digital Forensic Engineering, 2008. SADFE '08. Third International Workshop on
  • Conference_Location
    Oakland, CA
  • Print_ISBN
    978-0-7695-3171-7
  • Type

    conf

  • DOI
    10.1109/SADFE.2008.12
  • Filename
    4545362